Creating and applying variable bias rules in rule-based optical proximity correction for reduced complexity

ABSTRACT

An optical proximity correction (OPC) based integrated circuit design system and method introduce a variable rule in which rules are specified in terms of multiple correction actions that yield acceptable results. This category of rules provides more degrees of freedom in actual application so that the rule-based OPC tool can intelligently select the proper valid rule that minimizes the OPC complexity or meets other objectives.

CROSS-REFERENCE TO RELATED APPLICATION

This application relates to U.S. Provisional Patent Application No.60/619,160 filed on Oct. 15, 2004 entitled METHOD FOR CREATING ANDAPPLYING VARIABLE BIAS RULES IN RULE-BASED OPTICAL PROXIMITY CORRECTIONFOR REDUCED COMPLEXITY.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates generally to a system and method fordesigning integrated circuits or migrating integrated circuit designsfrom one technology node to another for fabrication by a semiconductormanufacturing process and, more particularly, to a system and method forproviding optical proximity correction for integrated circuit designlayouts.

2. Description of the Prior Art

The semiconductor manufacturing industry is continually evolvingsemiconductor device designs and fabrication processes and developingnew processes to produce smaller and smaller geometries of the designsbeing manufactured. Semiconductor devices constituted by smallergeometries typically consume less power, generate less heat, and operateat higher speeds than those having larger geometries. Moreover, smallergeometries allow silicon chips to contain more circuit elements, and,hence, the integrated circuit (IC) can be more complex, and more copiesof the same die can be produced on a single silicon wafer. Currently, asingle IC chip may contain over one billion geometries. Consequently, ICdesigns and semiconductor fabrication processes are extremely complex,since hundreds of processing steps may be involved. Occurrence of amistake or small error at any of the design or process steps maynecessitate redesign or cause lower yield in the final semiconductorproduct, where yield may be defined as the number of functional devicesproduced by the process as compared to the theoretical number of devicesthat could be produced assuming no bad devices.

Improving time-to-market and yield is a critical problem in thesemiconductor manufacturing industry and has a direct economic impact onthe semiconductor industry. In particular, a reduced time-to-market andhigher yield translate into earlier availability and more devices thatmay be sold by the manufacturer.

IC design layouts consist of a number of geometries in the form ofpolygons. Polygons are used to construct different features that arecomposed of portions of or whole polygons that are typicallycharacterized by certain geometric properties such as dimensions. Eachfeature constitutes one or more shapes that represent one or more edgesof a feature. A combination of features adjacent to each other forms atopological configuration that is often referred to as a pattern, orstructure. Therefore, the IC layout can also be viewed as constituting anumber of repeated patterns, and any number of such patterns constitutesa portion of the IC layout. These patterns of IC layouts are transferredto the silicon wafer predominantly through a process called lithography.In the most commonly used lithographic process referred to asphotolithography, a mask or reticle having transparent and opaqueregions representing structures in one IC layer is illuminated by alight source. The light emanating from the mask is then focused on aphotoresist layer applied to the wafer. Then the wafer is developed tohave portions of the resist removed and portions of the wafer etched,forming the geometrical patterns as desired. Typically, for IC designswith large feature dimensions, the patterns on the design are accuratelytransferred to the mask, and then accurately transferred to the waferthrough the lithography process, culminating in a phenomenon commonlyreferred to as WYSIWYG (“What you see is what you get”).

With ever decreasing feature sizes, increasing pattern densities, anddifficulty experienced in the advancement of IC manufacturing equipment,manufacturing of modern IC designs has encountered substantialimpediments and concomitant yield problems within the near- andsub-wavelength regime, where the feature dimension is at or below thewavelength of the light source. Diffraction-limited imaging in the near-and sub-wavelength regime has caused the classical WYSIWYG paradigm todisappear. With the emergence of near- and sub-wavelength lithography,patterns projected to the wafer through the lithography process areseverely distorted. Typical distortions include line edge displacement,which is common for line edge shapes; corner rounding, which isexhibited by corner shapes, and line end shortening, which isexperienced with line end shapes, as illustrated in FIG. 1( a).

In view of the widening gap between design and manufacturability in thenear- and sub-wavelength regime, the use of optical resolutionenhancement techniques (RET) such as optical proximity correction (OPC)is prevalent in many of the design and manufacturing schema to producefeature sizes of 0.18 μm and smaller. Typically, a design tape-out, inthe form of, for example, GDSII, is input to the RET implementation,e.g., an OPC data conversion, which generates new GDSII data using theinput GDSII design tape-out as a reference.

OPC is a process in which the physical layout from design tape-out ismodified to compensate for the pattern distortion caused by opticaldiffraction, resist development, etch, and other undesirable effectsthat occur during the lithography process. There are two knownapproaches to OPC. One is rule-based OPC, in which case correction rulesare determined ahead of time, which specify how different geometricalshapes should be modified according to some simple measures associatedwith the shapes being considered, for example, feature width andspacing. There are predominantly three types of rule-based OPC. One typeis hammerhead, that will be applied to line end shapes, as shown in FIG.1( d), which corrects for line end shortening. Another type is serif,that will be applied to corners, as shown in FIG. 1( e), which correctsfor corner rounding. The last type is edge bias, which corrects for lineedge displacement, as shown in FIG. 1( f). The bias correction is a moregeneric form of correction, as more complex corrections can berepresented by a collection of individual edge biases. For example, theserif or hammerhead corrections can be viewed as applying individualbiases to two or three consecutive edge segments, with corners filled,as illustrated in FIG. 1( g) for the case of a serif. One polygon cancontain a multitude of shapes that demand all three types of correction,as demonstrated in the example shown in FIG. 1( b). Rule-based OPC isusually geometry-based, and is simple and fast. However, rule-based OPCis not very accurate, and, hence, is used only for 0.25 μm or largertechnology nodes or on non-critical layers of more advanced technologynodes (0.18 μm or smaller), such as metal, or layers that contain onlyrelatively large geometries whose accuracy requirements are morerelaxed. Moreover, generation of correction rules is non-systematic andoften requires experience, and as the complexity of the geometriesincreases, the number of rules and possibly complexity of the rulesincrease as well, which makes them difficult to maintain.

The other OPC approach is model-based OPC. In model-based OPC, alithography model, which captures the effects of optics and the generallayout to the silicon pattern transfer process, is used to simulate thelayout patterns and predict the corresponding patterns on the wafer,based on which the required correction to each geometrical shape iscalculated and applied. The lithography model consists of a) an opticalmodel and b) other process effects including chemical, etching, andother factors. An optical model typically operates within a finite rangecalled a proximity range. When the optical image is simulated for alocation, commonly referred to as an evaluation point, only layoutgeometries within a radius of the proximity range centered around theevaluation point are considered, and those geometries outside of therange are ignored. A calibrated lithography model incorporates theoptical model and the other process effects. To obtain a calibratedmodel, test masks are illuminated, wafer images are formed, andmeasurements are made, followed by data fitting. The lithography modelis independent of physical layout.

The model-based OPC process typically involves a step referred to asdissection, where polygon edges are broken into edge segments which canbe moved individually to correct each segment. Evaluation points arespecified on the segments where the models are evaluated to calculatecertain wafer characteristics, such as edge displacement, as illustratedin FIG. 1( c). The required edge movement is calculated on-the-fly sothat the simulated edge displacements are minimized. Due to the use of amodel and a correction algorithm, the correction does not requirecorrection rules a priori, and is usually more accurate than onecorrected by a rule-based approach. On the other hand, due to finergranularity of the correction, the resulting corrected layout by amodel-based approach is typically more complex than that by a rule-basedapproach. Accordingly, full model-based OPC is generally used forcritical layers of designs of 0.18 μm or smaller.

Following the OPC step, the data undergoes a mask data preparation (MDP)step where the data will be fractured, the result of which is used towrite masks. Two main writing approaches are used today for maskmanufacturing. For the first approach referred to as “raster-scan”, anelectron or optical beam is scanned across the mask and turned on wherethe mask should be exposed. For the second approach referred to as“vector-scan”, a shaped e-beam is exposed at certain coordinatesrepresenting the data on the mask where the mask should be exposed. Theshaped beam exposure tools usually require the data to only contain acertain set of angles. Typically, these angles are 45-degree, 90-degree,and 135-degree angles because of the restriction of the shapes that canbe produced by the exposure tool. In this write approach, an MDP step isfracturing which involves taking complex shaped polygons and splittingthem up into smaller primitives, typically trapezoids, which can bewritten by the mask writer. FIG. 2 illustrates examples of fracturingpolygons into combinations of rectangles. The total number of primitivesafter fracturing for an IC layout is called “shot count”, or “figurecount”. In shaped beam exposure tools, a significant portion of thetotal mask write time is directly proportional to the shot count. Longermask write time means longer turnaround time, longer usage and wear ofthe exposure tools, and, hence, higher mask cost. Consequently, from themask cost perspective, the fewer the shot count, the better. On theother hand, OPC typically introduces more complexity to the layoutgeometries which leads to dramatic shot count increases. In FIG. 2, forexample, the original polygon 1100, with six vertices, can be fracturedinto two rectangles 1101 and 1102. After OPC, the resulting polygon1200, which has 28 vertices, is fractured into 12 rectangles 1201through 1212, a six-fold increase. Moreover, two slivers 1203 and 1205are also created. These small slivers lead to exposure dose inaccuracieswhen the mask is exposed, which in turn results in dimensioninaccuracies. If a simpler OPC can be applied without significantlycompromising accuracy, then the shot count can be reduced and sliverscan be removed. Again referring to FIG. 2, if the OPC can be simplifiedsuch that the small correction jogs 1001, 1002, and 1003 can be removed,then the resulting OPC output 1300, which contains 22 vertices, isfractured into 9 rectangles, a 25% savings in shot count, withoutproducing slivers.

Part of the reason that rule-based OPC is more attractive thanmodel-based OPC is that rule-based OPC typically creates less complexpolygons than model-based OPC, which leads to lower shot counts, and,consequently, lower mask cost. However, even with rule-based OPC, someenvironmental configurations can still lead to OPC output that is lessfracture-friendly. FIG. 2 shows a polygon 1400 with three neighboringfeatures 1410, 1411, and 1412. A typical rule-based OPC usingwidth-space formulae will create the following OPC features: hammerhead1401, outer-serifs 1402, 1403, and 1404, inner-serif 1405, and biases1406, 1407, 1408, and 1409. The different biases 1406 and 1407 are dueto a spacing change caused by a geometry 1410, whereas the differentbiases 1408 and 1409 are due to a spacing change caused by a geometry1411. Moreover, the existence of a geometry 1412 causes the serif 1404to be different from serifs 1402 and 1403. This OPC result leads to afracturing result of 11 rectangles 1501-1511, as shown in FIG. 2. Asliver 1503 is created as the result of misalignment between the biasjump from 1406 to 1407 and that from 1408 to 1409.

This fracture-unfriendly rule-based OPC is due to the strict applicationof a “best” correction or bias amount in accordance with the correctionrule that would render the most accurate result, which inevitablyintroduces correction jogs when neighboring environment changes arepresent. Current techniques for further simplifying the OPC outputinvolve a smoothing step, where non-smooth corrections consist ofmultiple correction jogs within some tolerance band, as shown in FIG. 3(a), are flattened to be free of jogs, as shown in FIG. 3( b). Thistechnique is ad hoc, as it does not provide ways to control the accuracyof the correction. In fact, it is possible that after such an alterationof the OPC output, the correction accuracy is also severely impacted.What is needed is a method of specifying correction rules and applyingthese rules in rule-based OPC that is more fracture-friendly andgenerates simpler OPC output without significantly compromisingaccuracy.

It is to this end that the present invention is directed. The variousembodiments of the present invention provide many advantages overconventional IC design methods and systems.

SUMMARY OF THE INVENTION

One embodiment of an optical proximity correction (OPC) based IC designsystem and method in accordance with the present invention provides manyadvantages over conventional design systems and techniques, which makethe IC design system and method for providing OPC in accordance with thepresent invention more useful to semiconductor manufacturers. Inaccordance with the various embodiments of the present invention, avariable bias rule is introduced in which rules are specified in termsof varying bias ranges or a set of discrete bias values, for example, ifthe biases are required to be on a certain grid that yield acceptableresults. This category of rules provides more degrees of freedom inactual application so that the rule-based OPC tool can intelligentlyselect the proper valid rule that minimizes the OPC complexity.

Accordingly, one embodiment in accordance with the present inventionprovides an IC design system and method for creating and applyingvariable bias rules in rule-based OPC for reduced OPC complexity. Inaccordance with the present invention, a system is provided to applyrule-based OPC where each rule is described by ranges of dependentvariables and a corresponding range of bias values, and the range is aset of all valid bias values, each causing the corrected features to bewithin a prespecified tolerance. Additionally, a method is provided forapplying rule-based OPC where each rule is described by ranges ofdependent variables and a corresponding set of valid bias values, eachcausing the corrected features to meet the required performanceobjective, where bias values are preferably selected from within therange or set of values so as to minimize the number of extra jogscreated.

The foregoing and other objects, features, and advantages of the presentinvention will become more readily apparent from the following detaileddescription of various embodiments, which proceeds with reference to theaccompanying drawing.

BRIEF DESCRIPTION OF THE DRAWING

The various embodiments of the present invention will be described inconjunction with the accompanying figures of the drawing to facilitatean understanding of the present invention. In the figures, likereference numerals refer to like elements. In the drawing:

FIG. 1, comprising FIGS. 1( a) through 1(g), illustrates the patterndistortion from the lithography process and application of opticalproximity correction (OPC);

FIG. 2 illustrates examples of fracturing polygons into combinations ofrectangles, and the increase of figure count and introduction of sliversby applying OPC to a simple geometry;

FIG. 3, comprising FIGS. 3( a) and 3(b), illustrates simplifying the OPCoutput in which non-smooth corrections consisting of multiple correctionjogs within some tolerance band are flattened to be free of jogs;

FIG. 4 is a block diagram illustrating an example of an IC design systemfor providing rule-based optical proximity correction (OPC) for reducedcomplexity in accordance with one embodiment of the present invention;

FIG. 5, comprising FIGS. 5( a) and 5(b), shows an example that comparesmultiple-valued rules in accordance with the various embodiments of thepresent invention and conventional single-valued rules and the possibleoutputs when the rules are applied with rule-based OPC in accordancewith one embodiment of the present invention;

FIG. 6 illustrates a range of values of bias that can lead to an edgeplacement error (EPE) that is within an optionally tightened tolerance;

FIG. 7 shows an example where jogs existing in a pre-OPC originalgeometry can even be removed after applying rule-based OPC in accordancewith the various embodiments of the present invention;

FIG. 8, comprising FIGS. 8( a) through 8(c), illustrates another examplein which completely smooth output cannot be obtained, but an output thatminimizes fracture count is possible;

FIG. 9 is a flow diagram for variable bias rule determination inaccordance with one embodiment of the rule-based OPC method of thepresent invention; and

FIG. 10, comprising FIGS. 10( a) through 10(i), illustrates handlingsmall exceptions when matching correction rule conditions or applyingcorrection rules in order to reduce correction complexity.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

The present invention is particularly applicable to acomputer-implemented software-based IC design system for generating anIC design using rule-based optical proximity correction (OPC) to correctan IC design layout, and it is in this context that the variousembodiments of the present invention will be described. It will beappreciated, however, that the IC design system and method for providingrule-based OPC for reduced complexity in accordance with the variousembodiments of the present invention have greater utility, since theymay be implemented in hardware or may incorporate other modules orfunctionality not described herein.

FIG. 4 is a block diagram illustrating an example of an IC design system10 for providing rule-based OPC for reduced complexity in accordancewith one embodiment of the present invention implemented on a personalcomputer 12. In particular, the personal computer 12 may include adisplay unit 14, which may be a cathode ray tube (CRT), a liquid crystaldisplay, or the like; a processing unit 16; and one or more input/outputdevices 18 that permit a user to interact with the software applicationbeing executed by the personal computer. In the illustrated example, theinput/output devices 18 may include a keyboard 20 and a mouse 22, butmay also include other peripheral devices, for example, printers,scanners, and the like. The processing unit 16 may further include acentral processing unit (CPU) 24, a persistent storage device 26, suchas a hard disk, a tape drive, an optical disk system, a removable disksystem, or the like, and a memory 28. The CPU 24 may control thepersistent storage device 26 and memory 28. Typically, a softwareapplication may be permanently stored in the persistent storage device26 and then may be loaded into the memory 28 when the softwareapplication is to be executed by the CPU 24. In the example shown, thememory 28 may contain an IC design tool 30 for providing rule-based OPC.The IC design tool 30 may be implemented as one or more software modulesthat are executed by the CPU 24.

In accordance with the present invention, the IC design system 10 forproviding rule-based OPC for reduced complexity may also be implementedusing hardware and may be implemented on different types of computersystems, such as client/server systems, Web servers, mainframecomputers, workstations, and the like. Now, more details of an exemplaryimplementation of the IC design system 10 in software will be described.

One embodiment of the present invention provides rule-based OPC for anIC design tape-out. For example, the IC design tape-out may be a GDS orOASIS file or a file having another format.

Various embodiments of the present invention provide a method ofspecifying correction rules not in terms of deterministic correction orbias values, but rather in terms of a set of valid correction or biasvalues from which the actual rule-based OPC processor can select. In oneembodiment of the present invention, the rule-based OPC processorselects correction or bias values from the set of available values andapplies the correction so as to minimize the complexity of the OPCoutput. In particular, the rule-based OPC processor applies correctionsso as to minimize the number of vertices in the OPC output.

Correction rules can be represented mathematically as R=f(C₁, C₂, . . .), where C₁, C₂, . . . are rule “conditions”. Possible conditions arepattern shapes (line ends or reverse line ends, inside or outsidecorners, jogs, etc.), pattern dimensions (width, spacing, height, etc.),circuit properties (gate, endcap, contact enclosure, etc.), and morecomplex characterization which combines any and all of the above. Therule R itself dictates an action to be performed on the pattern, such asmoving an edge toward the outside by a certain amount (bias), adding aserif of a certain size (a serif contains two bias values), adding ahammerhead of a certain size (a hammerhead contains three bias values),or more complex actions that combine one or more of these actions (e.g.,bias up the poly lines and bias down the diffusion by the same amount).The complete rule set may contain complex rules which have differentformulations (different c_(i) specifications, different form of f, anddifferent R). The complete rule set can be easily represented in tabularform, with c_(i)'s being the columns of “keys”, and R being the columnof values (as in a database).

A more concise and commonly used form of rules used in rule-based OPC isone in which the form of a correction rule can be represented as afunction of multiple variables, (b₁, b₂, . . . , c₁, c₂, . . . )=f(g₁,g₂, . . . , d₁, d₂, . . . ), where g_(i) are types of shapes such asline edge, line end, corners, gates, contact enclosures, or patternsidentified by complex Boolean or geometrical operations across multipledesign layers; and d_(i) are dimensions such as width, spacing, height,enclosure margin, or functions of multiple measured dimensions through acomplex formula. The output of the rule is a bias correction quantityb_(i), which provides correction to be applied to such patterns,together with additional parameters c_(i), which identify precisely theportion of the shape to which the bias is to be applied. Typically, theshapes are pre-selected (e.g., an edge or a portion of the edge) suchthat no further breakdown of the shape is allowed and the rule functionsimplifies to (b₁, b₂, . . . )=f(g₁, g₂, . . . , d₁, d₂, . . . ). If theshape consists of a single edge segment, then the rule functionsimplifies to b=f(g₁, g₂, . . . , d₁, d₂, . . . ), where b is the biasto be applied to the edge segment. This is a generic representation,since as explained in the prior art section, other more complex shapescan be broken down into a collection of single edge segments.Represented in table format, each rule contains “key” columns consistingof g₁, g₂, . . . , d₁, d₂, . . . , and the “value” column includes b. Inother word, each rule is a mapping between the values of the dependentvariables and a bias value. In a most popular form of classical ruletable, the dependent variables are typically partitioned into intervals.The smaller the interval, the more precise the rules are, but the largerthe rule table is. An example of one such rule table is as follows:

Width (w) Spacing (s) Bias (b) 200 ≦ w < 250 400 ≦ s < 500 5 250 ≦ w <300 400 ≦ s < 500 3 250 ≦ w < 300 600 ≦ s < 600 1 . . . . . . . . .

Complete rules to be applied to an IC layout may consist of a multitudeof sets of rules, with a different condition specified for each set ofthe rules. For example, the rules for correcting poly layers may consistof three sets of rules, one applies to transistor gates (a condition foridentifying the applicable poly patterns), another applies to poly linesthat are at least a certain distance away from diffusion (anothercondition for identifying the applicable poly patterns), and theremainder of the poly patterns (a third condition for identifying theapplicable poly patterns). Then, different patterns will be identifiedusing the conditions, and the corresponding rule set will be used whenapplying rule-based OPC for these patterns.

Conventional rule-based OPC solutions are based on one deterministicaction per matching condition and typically do not consider thecomplexity of the OPC output. For example, in rules where the correctionis a bias amount, there is a single bias value associated with eachcorrection rule, as demonstrated in the previous example (the rule tableabove). In the case of tabular format, each rule entry has a singlecorrection value. This can lead to jogs in the corrected output when anedge experiences width or space transition, as shown in FIG. 5( a).

In accordance with the present invention, at least one correction ruleis characterized by at least two, but possibly more, correction actionsfor a set of condition specifications. In the more generic forms, suchmulti-valued rules may be represented by ({R})=f(C₁, C₂, . . . ), where{R} is the set of all possible corrections. For example, {R}={R₁, R₂, .. . } means that the set of correction actions is a collection ofdistinct correction actions R₁, R₂, . . . . As another example,{R}=[bmin,bmax], in which case the correction action is a bias amountthat can have an arbitrary value from bmin to bmax. During the actualcorrection, one action is selected in order to achieve a presetobjective, typically, reduced mask complexity.

Determination of a rule may be either simulation-based or manual. Thesimulation-based approach is an automatic way for obtaining biases. Theco-pending U.S. patent application entitled MODEL-BASED PATTERNCHARACTERIZATION TO GENERATE RULES FOR RULE-MODEL-BASED HYBRID OPTICALPROXIMITY CORRECTION, application Ser. No. 11/221,528 filed on Sep. 8,2005, the disclosure of which is hereby incorporated herein in itsentirety by this reference, describes a systematic way of generatingrules using simulations. For example, this approach simulates thepattern with the specified width and spacing and determines a bias valuethat yields the smallest edge placement error (EPE). If one specifies anEPE tolerance range, which can be optionally further tightened asexplained in that patent application, then as illustrated in FIG. 6,there is a range of values of bias that can lead to an EPE that iswithin the optionally tightened tolerance. This range is referred to asthe “variable bias range”. In principle, any bias value within thisrange can be selected by the rule-based OPC processor to be applied.Practically, there may be additional constraints (such as a correctiongrid) that limit this range to a few distinct values (for example, allinteger values within this range). Within this variable bias range,there is one value that is considered “optimal”. Such optimal bias isusually based on metrics such as EPE (where the optimal bias wouldrender the smallest absolute value of the EPE, as shown in FIG. 6),image slope, mask error enhancement factor (MEEF), etc. The conventionalrule-based OPC is based on a single bias value which is typically onesuch optimal bias. The embodiments of the present invention introduce avariable bias rule format that allows a selection of a bias value withinthe variable bias range or from a collection of multiple bias values.This extra freedom for selecting the rule-based OPC may be applied so asto minimize the complexity of the OPC result.

FIG. 5 shows an example that compares the use of the new multiple-valuedrules and the conventional single-valued rules when applying rule-basedOPC. A pattern with width w0 has varying neighboring spacing s1 and s2.Suppose s1 and s2 are sufficiently far apart that they fall intodifferent spacing intervals in the rule table. In applying thesingle-valued rule in FIG. 5( a), the bias values corresponding to(w0,s1) and (w0,s2) are different, resulting in a jog at the spacingtransition location after the application of rule-based OPC. Thisintroduces two new vertices in the output. However, even when s1 and s2are different, the corresponding variable bias range for (w0,s1) and(w0,s2) may overlap, as illustrated in FIG. 5( b). Consequently, therule-based OPC in accordance with one embodiment of the presentinvention selects a single bias value that falls into both bias ranges.This bias value will be valid for both situations. The result is asingle bias value without introducing any new vertices. This results insimplified OPC.

FIG. 7 shows an example where jogs existing in a pre-OPC originalgeometry can even be removed after applying the rule-based OPC inaccordance with one embodiment of the present invention. As shown inFIG. 7, the jogs cause transitions in both pattern width and spacing,resulting in two width/spacing pairs (w1,s1) and (w2,s2), whichcorresponds to two different rules in the rule table. A bias b1 can beselected from [b1min,b1max] and a bias b2 can be selected from[b2min,b2max], such that the difference between b1 and b2 is equal tothe size of the jog, as shown in FIG. 7, so that with the application ofthe biases, the result is jog free. The result is an OPC output thatactually removes four original vertices constituting the two jogs.

FIG. 8 is another example in which completely smooth output cannot beobtained, but an output that minimizes figure count is possible. Theoriginal feature has a width transition from w1 to w2 and a spacingtransition from s1 to s2. This results in three rule entriescorresponding to (w1,s1), (w2,s1), (w2,s2), with bias ranges of[b1min,b1max], [b2min,b2max], and [b3min,b3max], respectively. If thethree bias ranges overlap, such that there exists a single bias valuethat falls into all three ranges, then such bias can be selected andapplied that avoids creating jogs. However, in this example, variablebias ranges [b1min,b1max] and [b3min,b3max] do not overlap, but the biasrange [b2min,b2max] overlaps with both. Then, considering the widthchange caused by the opposite edge, the rule-based OPC in accordancewith one embodiment of the present invention selects a single bias valuefrom the intersection of [b2min,b2max] and [b3min,b3max], and anarbitrary bias from [b3min,b3max] to be applied to the three edges. Ajog will be created in the output, but the jog is aligned with the jogon the opposite side, as shown in FIG. 8( c), and after fracturing, noextra figure is created. If three different bias values were used forthe three width and spacing conditions, as in conventional rule-basedOPC (shown in the dashed lines in FIG. 8( a)), then an extra figurewould be created after fracturing, as shown in FIG. 8( b).

FIG. 9 is flow diagram for applying rule-based OPC from a variable ruleset that minimizes the OPC output complexity. The key is, instead ofadopting a rule table in which each rule consists of a single correctionaction that optimizes the performance objective, e.g., minimizing EPE,the rule-based OPC uses a variable rule set in which each rule consistsof several correction actions that the rule-based OPC can select from,that all achieve a performance objective within tolerance, and selectsthe correction action that results in the simplest OPC output. As shownin FIG. 9, in a first step 8001, pattern properties are extracted foreach shape in the layout (such as width, spacing, pattern type, etc.).Then, the correction actions are looked up in the rule table orcalculated according to the rule formula in a step 8002. With correctionactions determined for each shape, some or all shapes will have morethan one correction action. In a step 8003, different possible outputswith combinations of different selections of correction actions areexamined. First, in a step 8004, the correction action is determined forthose shapes that, after applying the rules, will create no new jogs orremove jogs in the original layout. For the remaining shapes, correctionjogs will be unavoidable no matter how the correction actions areselected. In an optional next step 8005, the correction actions aredetermined for those remaining shapes in which, after applying therules, the resulting jogs are aligned with the vertices of the opposingshape (which avoid creating an extra figure during fracturing). For theremainder of the shapes, the OPC output will not be simplified byselection of correction actions, and, hence, the optimal correctionaction will be applied to those shapes, as in conventional rule-basedOPC. For example, the correction action that leads to the smallestabsolute value of EPE will be applied. As shown in FIG. 9, the newlyintroduced steps 8003-8005 as compared to conventional rule-based OPCtake advantage of the selection of the correction rules that generateless complex OPC output.

One contemplated modification of this method is reducing the variablebias rules into single bias rules through rule-merging with the goal ofreducing correction variations and avoiding jog creation. For example,suppose there are four rules from a rule set shown in tabular form as:

Width range Spacing range Height range Bias range 300–350 400–450800–900 5–10 350–400 400–500 800–900 2–6  300–350 450–500 800–900 6–11300–400 500–600 800–900 4–8 These four rules can be merged into a single rule as:

Width range Spacing range Height range Bias range 300–400 400–600800–900 6This rule demonstrates that for any feature in the height range of800-900 nm having a width variation within 300-400 nm and a spacingvariation within 400-600 nm would lead to the same 6 nm bias. Hence, forfeatures having a width or spacing transition within these ranges, noextra jog will be created after rule-based OPC.

Another embodiment of the present invention involves adding allowance ofsmall exceptions when matching or applying correction rule conditions inorder to reduce correction complexity. FIG. 10 shows several examples.FIG. 10( a) shows a pattern in which there are three width/spacing pairsmeasured: (w1,s1), (w2,s2), and (w3,s3), where (w1,s1) and (w2,s2) haveassociated rules r1 and r2, respectively (both are ranges as shown indashed boxes). There are no rules associated with (w3,s3), whichseparates the two edges. If one applies OPC strictly according to therules, then the result is a correction shown in FIG. 10( b), where onejog in the original shapes is replaced by two jogs in corrected shapes.However, when the part of the edges associated with (w3,s3) is small(i.e., h is shorter than a prespecified tolerance), then the rule-basedOPC can ignore this small exception and extend the edge that matches r2to include this small segment. In this case, the rule-based OPC canselect corrections such that the jog in the original shape is removed,as shown in FIG. 10( c), because the bias ranges for r1 and r2 overlap,as shown in FIG. 10( a). FIG. 10( d) shows another example where theoriginal geometry 1601 has a small jog 1603 along with an edge 1602. Theedge 1602 has width w and spacing s that satisfies the condition of arule which has a corresponding bias range [bmin,bmax]. The jog has awidth w1 and spacing s1 which finds no matching rule in the rule table.Consequently, a rule-based OPC correction based on strict rule matchingwill select a bias amount from the range [bmin,bmax] and produce acorrection 1604 shown in FIG. 10( e), where the original jog is stillpresent and uncorrected. However, if the size of the jog h is small, therule-based OPC can extend the correction to cover this jog, resulting ina correction 1605 shown in FIG. 10( f) that has a smooth output, with nojog. In yet another example shown in FIG. 10( g), the original feature1611 has a width of w and no jog, but the neighboring feature 1620 leadsto a spacing transition along the feature 1611 from s to infinite. Theportion of the edge 1612 with width w and spacing s finds a matchingrule with a bias range [bmin,bmax], whereas the remaining portion of theedge 1613 is of width w, spacing infinity, and a small size h, and findsno matching rule. Consequently, a rule-based OPC correction based onstrict rule matching will select a bias amount from the range[bmin,bmax] and produce a correction 1614 shown in FIG. 10( h), whichintroduces a jog that is non-existent in the original feature. However,if the size of unmatched edge portion h is small, the rule-based OPC canextend the correction to cover this portion with the same bias amount,resulting in a correction 1615 shown in FIG. 10( i) that has a smoothoutput, with no jog.

So far in the selection of correction actions for each rule therule-based OPC has focused on making the selections to minimize OPCoutput complexity. It does, however, not exclude the use of otherobjectives for rule-based OPC in making the selection, including thosethat are compatible with the traditional “optimal” correction action.For example, the rule-based OPC can select correction actions based onminimizing the absolute value of the EPE or CD error, maximizing theimage slope or contrast, maximizing dose or defocus latitude, orminimizing sensitivity to aberration or mask error enhancement factor(MEEF). The rule-based OPC may also choose to adopt different objectivesfor different types of patterns, for example, minimizing EPE fortransistor gates, maximizing image slope for small critical dimensionfeatures, and minimizing OPC output complexity for large criticaldimension features.

While the foregoing description has been with reference to particularembodiments of the present invention, it will be appreciated by thoseskilled in the art that changes to these embodiments may be made withoutdeparting from the principles and spirit of the invention. Accordingly,the scope of the present invention can only be ascertained withreference to the appended claims.

1. A correction rule specification method in which the correction ruleis used for rule-based optical proximity correction (OPC), comprising:specifying at least one correction rule R for rule-based OPC whichcomprises of a set of conditions C₁, C₂, . . . representedmathematically as R=f(C₁, C₂, . . . ), where C₁, C₂, . . . areconditions and f indicates that said at least one correction rule forrule-based OPC is dependent on said conditions, wherein said at leastone correction rule for rule-based OPC has at least one correctionaction that has a range or set of correction values; and selecting, byusing a computer, an optimal correction value from the range or set ofcorrection values for a shape of an integrated circuit layout, thatresults in optimal OPC output for reduced complexity using rule-basedOPC; wherein the selecting includes determining the optimal correctionvalue by determining a first correction value from the range or set ofcorrection values that overlaps a second correction value of a secondcorrection rule whereby the optimal correction value, when applied tothe shape as rule-based OPC, would not introduce any new vertices in theshape; or wherein the selecting includes determining the optimalcorrection value by determining the first or a third correction valuefrom the range or set of correction values if the range or set ofcorrection values does not overlap the second correction value wherebythe optimal correction value, when applied to the shape as rule-basedOPC, would minimize figure count.
 2. The method of claim 1 wherein theconditions are parameterized and specified in terms of a rule table. 3.The method of claim 1 wherein the at least one correction action isparameterized and specified in terms of the amount of edge movement. 4.The method of claim 3 wherein the at least one correction rule forrule-based OPC is specified in terms of the amount of edge movement thatis given in a set of discrete numbers.
 5. The method of claim 3 whereinthe at least one correction rule for rule-based OPC is specified interms of the amount of edge movement that is given by at least onecontinuous range.
 6. The method of claim 3 wherein a correction actionis specified by two parameters representing the amount of edge movementof the two edges of a corner such that the result of the correctionafter application of the correction rule is a serif.
 7. The method ofclaim 6 wherein at least one amount of edge movement is given in a setof discrete numbers.
 8. The method of claim 6 wherein at least oneamount of edge movement is given in a set of continuous ranges.
 9. Themethod of claim 3 wherein a correction action is specified by threeparameters representing the amount of edge movement of the three edgesof a line end such that the result of the correction after applicationof the correction rule for rule-based OPC is a hammerhead.
 10. Themethod of claim 9 wherein at least one amount of edge movement is givenin a set of discrete numbers.
 11. The method of claim 9 wherein at leastone amount of edge movement is given in a set of continuous ranges. 12.The method of claim 1 wherein the at least one correction rule forrule-based OPC is applied by rule-based OPC to an integrated circuitlayout by selecting one correction rule from a set of correction rules.13. The method of claim 12 wherein the selection of a correction rulefor rule-based OPC is based on minimizing the complexity of the output.14. The method of claim 13 wherein minimizing the complexity of theoutput comprises minimizing the number of vertices that can be createdby avoiding creation of jogs when applying more than one correction rulefor rule-based OPC on the same polygon edge.
 15. The method of claim 13wherein minimizing the complexity of the output comprises minimizing thenumber of vertices that can be created by removing jogs in the originallayout geometries when applying one or more correction rules forrule-based OPC on multiple edges.
 16. The method of claim 13 whereinminimizing the complexity of the output comprises aligning the verticescreated on the edge with their opposite vertices which avoid creation ofextra fracturing figures.
 17. The method of claim 13 wherein minimizingthe complexity of the output comprises allowing exceptions to correctionrules for rule-based OPC and extending corrections for exception shapesby rule-based OPC which eliminate vertices that would otherwise becaused by exception shapes in the OPC output.
 18. The method of claim 17wherein the exception shape is a shape having a height or width notexceeding a prespecified threshold.
 19. The method of claim 12 whereinthe selection of a correction rule for rule-based OPC is based onobtaining the smallest absolute value of edge placement error (EPE) forthe applicable edge.
 20. The method of claim 12 wherein the selection ofa correction rule for rule-based OPC is based on obtaining the largestabsolute value of intensity slope for the applicable edge.
 21. Themethod of claim 12 wherein the selection of a correction rule forrule-based OPC is based on obtaining the optimal focus latitude for theapplicable edge.
 22. The method of claim 12 wherein the selection of acorrection rule for rule-based OPC is based on obtaining one of thegroup of performance metrics consisting of the smallest value of maskerror enhancement factor (MEEF), smallest value of sensitivity toaberration, and the largest image contrast.
 23. A rule-based opticalproximity correction (OPC) system comprising instructions stored on orin a computer-readable storage medium and executed by a processor, theinstructions comprising: instructions for specifying at least onecorrection rule R for rule-based OPC consisting of a set of conditionsC₁, C₂, . . . represented mathematically as R=f(C₁, C₂, . . . ), whereC₁, C₂, . . . are conditions and f indicates that said at least onecorrection rule for rule-based OPC is dependent on said conditions,wherein said at least one correction rule for rule-based OPC has atleast one correction action that has a range or set of correctionvalues; and instructions for selecting an optimal correction value fromthe range or set of correction values for a shape of an integratedcircuit layout, that results in optimal OPC output for reducedcomplexity using rule-based OPC; wherein the instructions for selectingincludes instructions for determining the optimal correction value bydetermining a first correction value from the range or set of correctionvalues that overlaps a second correction value of a second correctionrule whereby the optimal correction value, when applied to the shape asrule-based OPC, would not introduce any new vertices in the shape; orwherein the instructions for selecting include instructions fordetermining the optimal correction value by determining the first or athird correction value from the range or set of correction values if therange or set of correction values does not overlap the second correctionvalue whereby the optimal correction value, when applied to the shape asrule-based OPC, would minimize figure count.
 24. The system of claim 23wherein the conditions are parameterized and specified in terms of arule table.
 25. The system of claim 23 wherein the at least onecorrection action is parameterized and specified in terms of the amountof edge movement.
 26. The system of claim 25 wherein the correction rulefor rule-based OPC is specified in terms of the amount of edge movementthat is given in a set of discrete numbers.
 27. The system of claim 25wherein the correction rule for rule-based OPC is specified in terms ofthe amount of edge movement that is given by at least one continuousrange.
 28. The system of claim 25 wherein a correction action isspecified by two parameters representing the amount of edge movement ofthe two edges of a corner such that the result of the correction afterapplication of the correction rule for rule-based OPC is a serif. 29.The system of claim 28 wherein the amount of edge movement is given in aset of discrete numbers.
 30. The system of claim 28 wherein the amountof edge movement is given in a set of continuous ranges.
 31. The systemof claim 25 wherein a correction action is specified by three parametersrepresenting the amount of edge movement of the three edges of a lineend such that the result of the correction after application of thecorrection rule for rule-based OPC is a hammerhead.
 32. The system ofclaim 31 wherein the amount of edge movement is given in a set ofdiscrete numbers.
 33. The system of claim 31 wherein the amount of edgemovement is given in a set of continuous ranges.
 34. The system of claim23, further comprising instructions for receiving an integrated circuitlayout wherein rule-based OPC correction is applied to the integratedcircuit layout.
 35. The system of claim 34 wherein the selection of acorrection rule for rule-based OPC is based on minimizing the complexityof the output.
 36. The system of claim 35 wherein minimizing thecomplexity of the output comprises minimizing the number of verticesthat can be created by avoiding creation of jogs when applying more thanone correction rule for rule-based OPC on the same polygon edge.
 37. Thesystem of claim 35 wherein minimizing the complexity of the outputcomprises minimizing the number of vertices that can be created byremoving jogs in the original layout geometries when applying one ormore correction rules for rule-based OPC on multiple edges.
 38. Thesystem of claim 35 wherein minimizing the complexity of the outputcomprises aligning the vertices created on the edge with their oppositevertices which avoid creation of extra fracturing figures.
 39. Thesystem of claim 35 wherein minimizing the complexity of the outputcomprises allowing exceptions to correction rules for rule-based OPC andextending corrections for exception shapes by rule-based OPC whicheliminate vertices that would otherwise be caused by exception shapes inthe OPC output.
 40. The system of claim 39 wherein the exception shapeis a shape having a height or width not exceeding a prespecifiedthreshold.
 41. The system of claim 34 wherein the selection of acorrection action is based on obtaining the smallest absolute value edgeplacement error (EPE) for the applicable edge.
 42. The system of claim34 wherein the selection of a correction action is based on obtainingthe largest absolute value of intensity slope for the applicable edge.43. The system of claim 34 wherein the selection of a correction actionis based on obtaining the optimal focus latitude for the applicableedge.
 44. The system of claim 34 wherein the selection of a correctionaction is based on obtaining one of the group of optimum performancemetrics consisting of the smallest value of mask error enhancementfactor (MEEF), smallest value of sensitivity to aberration, and thelargest image contrast.